Package: hypervolume
Type: Package
Title: High Dimensional Geometry, Set Operations, Projection, and
        Inference Using Kernel Density Estimation, Support Vector
        Machines, and Convex Hulls
Version: 3.1.3
Date: 2023-09-13
Author: Benjamin Blonder, with contributions from Cecina Babich Morrow, Stuart Brown, Gregoire Butruille, Daniel Chen, Alex Laini, and David J. Harris
Maintainer: Benjamin Blonder <benjamin.blonder@berkeley.edu>
Description: Estimates the shape and volume of high-dimensional datasets and performs set operations: intersection / overlap, union, unique components, inclusion test, and hole detection. Uses stochastic geometry approach to high-dimensional kernel density estimation, support vector machine delineation, and convex hull generation. Applications include modeling trait and niche hypervolumes and species distribution modeling.
License: GPL-3
Depends: Rcpp, methods, R (>= 3.5.0)
LinkingTo: Rcpp, RcppArmadillo, progress
Imports: raster, maps, MASS, geometry, ks, hitandrun, pdist,
        fastcluster, compiler, e1071, progress, mvtnorm, data.table,
        terra, sp, foreach, doParallel, parallel, ggplot2, pbapply,
        palmerpenguins, purrr, dplyr, caret
Suggests: rgl, magick, alphahull, knitr, rmarkdown, gridExtra
NeedsCompilation: yes
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Packaged: 2023-09-14 09:30:45 UTC; benjaminblonder
Repository: CRAN
Date/Publication: 2023-09-14 10:20:02 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 03:12:55 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
